Jeju Island, Korea
October 4-8, 2004

Kenichi Yoshida, Kazuyuki Takagi, Kazuhiko Ozeki

The University of Electro-Communications, Japan

In our previous paper, we presented a speaker identification system
using a multi-SNR multi-band method, and reported its robustness
against environmental noises. This paper describes two modifications
to the system for further enhancement of its noise-robustness. Firstly,
1/f noise is employed instead of white Gaussian noise to make noisy
data for training multi-SNR GMMs. Secondly, recombination
weights for subband likelihood are automatically adjusted based on
the estimated subband noise power. For performance evaluation,
text-independent speaker identification experiments were conducted on
test speech data created by mixing clean speech data with 5 kinds of
environmental noises: "bus", "car", "office", "lobby", and
"restaurant" at 0 and 10 dB SNRs. By the two modifications, the
identification error rate was reduced 30.3% on the average compared
with the baseline multi-SNR multi-band method using white
Gaussian noise and equal weights.